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Hey, at work we have been forced to use Denodo. How does this compare to Denodo? Seems a lot better and doesn’t try to do any “data virtualization”. I am a bit

by kfk 7y ago

Hey, at work we have been forced to use Denodo. How does this compare to Denodo? Seems a lot better and doesn’t try to do any “data virtualization”. I am a bit scared by the query optimizer because the Denodo one is super buggy. Overall I think the concept is great and this might be a great companion to etl tools.

minxomat 7y ago
If vis is the focus, I'd recommend Postgres FDW over anything else here, just because PG is supported by almost every vis software (metabase, redash, many Apache projects, Tableau, Google Data Studio (free) etc.)
- stevepike 7y ago
  I've been working on a new company that's doing cloud hosted postgres foreign data wrappers as a service (plus a bunch of interface / workflow stuff on top) and while I'm biased I totally agree. The postgres FDW system has gotten very sophisticated in later releases. It does performance optimizations like pushing down filters / aggregates, and it even goes further by supporting sending remote explain calls out to the underlying datasources to use in query planning. In one of my local tests vs. Denodo it smartly decided _not_ to push a group by down when the cardinality of the column being grouped on is very high (since the grouping doesn't reduce the number of rows sent over the wire very much), which blew me away. If anyone is interested I'd love to chat: steve (at) syndetic.co
cube2222 7y ago
Hey, I have no idea really. I've never used Denodo and a quick glance at their homepage doesn't tell much so I don't understand what they mean with data virtualization. We're obviously surely not as battle tested, this being the initial release, but hopefully we'll be able to compare favorably! The query optimizer is kinda simple currently. Mostly pushing down filters under maps and pushing supported workloads down to the datasources. Though I don't know how it will evolve going further ;)
sixdimensional 7y ago
I used to work for a competitor to Denodo. Query optimization for data virtualization/federation across heterogenous systems is very complicated - that much I can assure you. You might be interested in Dremio (which is a modernized and open source version of Drill, but also has a commercial version) too. I had previously studied Spark, PrestoDb and Hive, among other things, for similar purposes. If you ever want to chat feel free to contact me via my profile email.

by kfk 7y ago

minxomat 7y ago

If vis is the focus, I'd recommend Postgres FDW over anything else here, just because PG is supported by almost every vis software (metabase, redash, many Apache projects, Tableau, Google Data Studio (free) etc.)

stevepike 7y ago
I've been working on a new company that's doing cloud hosted postgres foreign data wrappers as a service (plus a bunch of interface / workflow stuff on top) and while I'm biased I totally agree. The postgres FDW system has gotten very sophisticated in later releases. It does performance optimizations like pushing down filters / aggregates, and it even goes further by supporting sending remote explain calls out to the underlying datasources to use in query planning. In one of my local tests vs. Denodo it smartly decided _not_ to push a group by down when the cardinality of the column being grouped on is very high (since the grouping doesn't reduce the number of rows sent over the wire very much), which blew me away. If anyone is interested I'd love to chat: steve (at) syndetic.co

cube2222 7y ago

Hey, I have no idea really. I've never used Denodo and a quick glance at their homepage doesn't tell much so I don't understand what they mean with data virtualization. We're obviously surely not as battle tested, this being the initial release, but hopefully we'll be able to compare favorably! The query optimizer is kinda simple currently. Mostly pushing down filters under maps and pushing supported workloads down to the datasources. Though I don't know how it will evolve going further ;)

sixdimensional 7y ago

I used to work for a competitor to Denodo. Query optimization for data virtualization/federation across heterogenous systems is very complicated - that much I can assure you. You might be interested in Dremio (which is a modernized and open source version of Drill, but also has a commercial version) too. I had previously studied Spark, PrestoDb and Hive, among other things, for similar purposes. If you ever want to chat feel free to contact me via my profile email.